This invention relates generally to merchant prediction systems, and more specifically, to methods and apparatus for implementing an ensemble merchant prediction system in relation to payment transactions conducted over a bankcard network on behalf of account holders.
Historically, the use of “charge” cards for consumer transaction payments was at most regional and based on relationships between local credit issuing banks and various local merchants. The payment card industry has since evolved with the issuing banks forming associations (e.g., MasterCard) and involving third party transaction processing companies (e.g., “Merchant Acquirers”) to enable cardholders to widely use charge cards at any merchant's establishment, regardless of the merchant's banking relationship with the card issuer.
For example, FIG. 1 of the present application shows an exemplary multi-party payment card industry system for enabling payment-by-card transactions. As illustrated, the merchants and issuer do not necessarily have to have a one-to-one relationship. Yet, various scenarios exist in the payment-by-card industry today, where the card issuer has a special or customized relationship with a specific merchant, or group of merchants.
Over 25 million merchants accept a form of payment card. Sometimes these merchants are affiliated with a more recognizable chain, brand, or other legal entity. In one example, a franchisee of a large multi-national fast food company may be identified to the transaction card issuer as “Chris's Restaurants, LLC”, and therefore there is no correlation to the franchisor. Consideration is now being given to ways of improving implementations in the payment-by-card industry. In particular, attention is being directed to utilizing historical transaction data to predict future financial card transactions and determine if there are correlations to be made from the data.
More specifically, merchant location data that is collected by companies is often assigned a higher-level grouping based on legal ownership, brand, or some other definition. Often these relationships are not explicitly defined or readily available. Deducing this relationship heretofore has involved manual inspection of the transaction data to discover a field or set of fields that can be used to qualify locations for membership to an appropriate grouping.